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IJSTR >> Volume 9 - Issue 1, January 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Performance Level Measurement Of Automatic Detection Of Glaucoma And Its Progressive Monitoring

[Full Text]

 

AUTHOR(S)

Sharanagouda Nawaldgi, Dr. Lalitha Y S

 

KEYWORDS

RLS Filter, DWT, Symlet, Biorthogonal and Daubechies wavelets, MLP-BP ANN.

 

ABSTRACT

One of the eye infections is glaucoma and its effects on the optic nerve and after some time end up genuine because of strain and pressure in the mind. The infections are caused inside the eye by the progression of intraocular pressure. The retina is a layer of tissue at the forefront of an eye that detects light and sends the signal to the mind. The infections are obtained and may not appear later in time. In the event that the infection is distinguished early, it stays away from the visual field setback. The essential Open Angle Glaucoma (OAG) management is a standout amongst the most critical and most difficult parts of the glaucoma location. The different discoveries that rely upon conclusion of glaucoma are intraocular weight, visual field misfortune, and optical nerve glass. Glaucoma recognition should be possible by different advances perimetry, tonometry, ophthalmoscopy, pachymetry, gonioscopy. To address the disease advanced methodologies are proposed such as prepossessing using RLS (Recursive least square) algorithm to improve the quality of the image. The image is obtained is low contrast and consists of speckle-noise which is difficult to analyze the image. The removal of this noise preprocessing is done. The evacuation of this commotion preprocessing is finished. The objective of research work is to build up a calculation for the programmed discovery of glaucoma infection and its arrangement for anomalous and typical eye pictures. To characterize the pictures as typical or strange the classifier clients are SVM, arbitrary woodland, ANN, SOM, and Naive Bays, for finding the better precision discover which classifier is useful for grouping of ordinary retinal pictures and glaucomatous pictures. Here, the blends of data from auxiliary and useful tests are engaged with the early finding of glaucoma. In the examination work vitality and basic highlights are considered. By utilizing 2D DWT (two dimension subgroups disintegration) vitality include extraction are done and the achievement is done using MATLAB. For the overall work of this paper, Graphical User Interface (GUI) is created to make user-friendly and to browse the database image for further process. Each stage of the operation is automatically applied for the next process until classifications. The proposed RLS filter will be a suitable approach for denoising the speckle noise from Glaucoma medical images. From these results, it can be seen that the proposed plain intensity filter has an improvement in MSE by 12%, SNR by 52%, PSNR by 25% and after classification of the database, the accuracy of the work is 92% as compared to the existing works in the literature.

 

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